156 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" uni jobs at Zintellect
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, program rules, and availability of the participant. Appointments will be conducted virtually. $125 per week stipend based on part-time participation each week. Program provides the opportunity to learn from
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in genetically modified maize hybrids. Outcomes will contribute long-term goals to develop tools to detect and monitor resistant insects in field populations. Learning Objectives: Participants will
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Engineering 1: Under the guidance of a mentor, this Lifecycle Engineering program area will teach you how to utilize chemical, biochemical, and systems engineering to develop and design solutions that continue
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is for STEM-focused undergraduates, and recent graduates, with a strong interest in STEM professions. Under the guidance of a mentor, you will learn how to utilize mechanical, electrical, computer, and
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and Data Science (including machine learning and AI for defense applications) - Systems Engineering and Engineering Management - Industrial Engineering and Production Management - Mathematical Modeling
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machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of
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. Learning Objectives: The Fellow will learn how wildland fire managers use weather and fuel data to plan and conduct prescribed burns. The Fellow will gain understanding of the range of meteorological data
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instrumentation and test systems. You will learn how to prepare test samples, participate in test events, analyze data and prepare reports. You will gain understanding of good laboratory practices, develop
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ecosystem services that they provide. Learning Objectives: The participant will learn to utilize ecological simulation models and to design and conduct geospatial analysis of model results to characterize
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well as preliminary research on yield prediction modeling. Learning Objectives: The participant will develop skills in agricultural predictive yield modeling. These will include analysis and interpretation of large UAV